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PubMed · 10248802

Ageism.

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R N Butler. 1980. Ageism.. https://pubmed.ncbi.nlm.nih.gov/10248802/

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The biochemical mechanisms by which regular exercise significantly benefits health and well being, including improved cognitive function, are not well understood. Four-week-old (young) and 14-month-old (middle aged) Wistar rats were randomly assigned to young control and young exercised, middle-aged control and middle-aged exercised groups. Exercise groups were exposed to a swimming regime of 1 h a day, 5 days a week for 9 weeks. The passive avoidance test showed that middle-aged exercised rats had significantly (P<0.05) better short- (24 h) and long-term (72 h) memory than aged-matched control rats. Conditioned pole-jumping avoidance learning was improved markedly in both age groups by exercise. Brain thiobarbituric acid-reactive substances and 8-hydroxy-2'deoxyguanosine content in the DNA did not change significantly, while the protein carbonyl levels decreased significantly (P<0.05) in both exercised groups. This decrease was accompanied by an increase in the chymotrypsin-like activity of proteasome complex in the exercised groups, whereas trypsin-like activity did not differ significantly between all groups. The DT-diaphorase activity increased significantly (P<0.05) in the brain of young exercised animals. These data show that swimming training improves some cognitive functions in rats, with parallel attenuation of the accumulation of oxidatively damaged proteins.

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Age-related changes in aggrecan glycosylation affect cleavage by aggrecanase.

Aggrecan degradation involves proteolytic cleavage of the core protein within the interglobular domain. Because aggrecan is highly glycosylated with chondroitin sulfate (CS) and keratan sulfate (KS), we investigated whether glycosylation affects digestion by aggrecanase at the Glu(373)-Ala(374) bond. Treatment of bovine aggrecan monomers to remove CS and KS resulted in loss of cleavage at this site, suggesting that glycosaminoglycans (GAGs) play a role in cleavage at the Glu(373)-Ala(374) bond. In contrast, MMP-3 cleavage at the Ser(341)-Phe(342) bond was not affected by glycosidase treatment of aggrecan. Removal of KS, but not CS, prevented cleavage at the Glu(373)-Ala(374) bond. Thus, KS residues may be important for recognition of this cleavage site by aggrecanase. KS glycosylation has been observed at sites adjacent to the Glu(373)-Ala(374) bond in steer aggrecan, but not in calf aggrecan (Barry, F. P., Rosenberg, L. C., Gaw, J. U., Gaw, J. U., Koob, T. J., and Neame, P. J. (1995) J. Biol. Chem. 270, 20516-20524). Interestingly, although we found that aggrecanase degraded both calf and steer cartilage aggrecan, the proportion of fragments generated by cleavage at the Glu(373)-Ala(374) bond was higher in steer than in calf, consistent with our observations using aggrecan treated to remove KS. We conclude that the GAG content of aggrecan influences the specificity of aggrecanase for cleavage at the Glu(373)-Ala(374) bond and suggest that age may be a factor in aggrecanase degradation of cartilage.

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Goodness-of-fit statistics for age-specific reference intervals.

The age-specific reference interval is a commonly used screening tool in medicine. It involves estimation of extreme quantile curves (such as the 5th and 95th centiles) of a reference distribution of clinically normal individuals. It is crucial that models used to estimate such intervals fit the data extremely well. However, few procedures to assess goodness-of-fit have been proposed in the literature, and even fewer have been evaluated systematically. Here we consider procedures based on the distribution of the Z-scores (standardized residuals) from a model and on Pearson chi(2) statistics for observed and expected counts in groups defined by age and the estimated reference centile curves. Two of the procedures (Q and grid tests) are mainly inferential, whereas the third (permutation bands and B-tests) is essentially graphical. We obtain approximations to the null distributions of several relevant test statistics and examine their size and power for a range of models based on real data sets. We recommend Q-tests in all situations where Z-scores are available since they are general, simple to calculate and usually have the highest power among the three classes of test considered. For the cases considered the grid tests are always inferior to the Q- and B- tests.

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